[MAJOR UPDATE]Added syllabled letters functionallity and added letters attributes to letter accetuation
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@ -4,7 +4,7 @@
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<change type="MODIFICATION" beforePath="$PROJECT_DIR$/cnn/word_accetuation/syllables/cnn.ipynb" afterPath="$PROJECT_DIR$/cnn/word_accetuation/syllables/cnn.ipynb" />
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<change type="MODIFICATION" beforePath="$PROJECT_DIR$/prepare_data.py" afterPath="$PROJECT_DIR$/prepare_data.py" />
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@ -35,8 +35,8 @@
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@ -156,13 +156,14 @@
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<find>generate</find>
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<find>shuffle</find>
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<find>X_</find>
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<find>dictionary</find>
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<find>create_dict</find>
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<find>split_content</find>
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<find>decode_position</find>
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<find>'r'</find>
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<find>decode</find>
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<find>complete_feature_dict</find>
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<find>dictionary</find>
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<find>voiced_consonants</find>
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@ -207,6 +208,8 @@
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@ -221,8 +224,6 @@
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@ -881,8 +882,8 @@
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131
prepare_data.py
131
prepare_data.py
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@ -310,9 +310,16 @@ def old_generate_full_matrix_inputs():
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# Generate each y as an array of 11 numbers (with possible values between 0 and 1)
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def generate_X_and_y(dictionary, max_word, max_num_vowels, content, vowels, accetuated_vowels, feature_dictionary, shuffle_vector_location, shuffle=True):
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def generate_X_and_y(dictionary, max_word, max_num_vowels, content, vowels, accetuated_vowels, feature_dictionary, shuffle_vector_location, shuffle=True, aditional_letter_attributes=True):
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y = np.zeros((len(content), max_num_vowels))
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X = np.zeros((len(content), max_word, len(dictionary)))
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if aditional_letter_attributes:
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X = np.zeros((len(content), max_word, len(dictionary) + 6))
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voiced_consonants = get_voiced_consonants()
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resonant_silent_consonants = get_resonant_silent_consonants()
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unresonant_silent_consonants = get_unresonant_silent_consonants()
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else:
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X = np.zeros((len(content), max_word, len(dictionary)))
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print('CREATING OTHER FEATURES...')
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X_other_features = create_X_features(content, feature_dictionary)
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print('OTHER FEATURES CREATED!')
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@ -327,6 +334,20 @@ def generate_X_and_y(dictionary, max_word, max_num_vowels, content, vowels, acce
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X[i][j][index] = 1
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break
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index += 1
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if aditional_letter_attributes:
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if is_vowel(el[0], j, vowels):
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X[i][j][len(dictionary)] = 1
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else:
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X[i][j][len(dictionary) + 1] = 1
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if c in voiced_consonants:
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X[i][j][len(dictionary) + 2] = 1
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else:
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X[i][j][len(dictionary) + 3] = 1
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if c in resonant_silent_consonants:
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X[i][j][len(dictionary) + 4] = 1
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elif c in unresonant_silent_consonants:
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X[i][j][len(dictionary) + 5] = 1
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j += 1
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j = 0
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word_accetuations = []
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@ -991,7 +1012,6 @@ def dict_occurances_in_dataset_rate(content):
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case_numbers = np.sum(X_other_features, axis=0)
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print(case_numbers)
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def get_voiced_consonants():
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return ['m', 'n', 'v', 'l', 'r', 'j', 'y', 'w']
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@ -1003,15 +1023,6 @@ def get_unresonant_silent_consonants():
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def split_consonants(consonants):
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# def voiced_consonants():
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# return ['m', 'n', 'v', 'l', 'r', 'j', 'y', 'w']
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#
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# def resonant_silent_consonants():
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# return ['b', 'd', 'z', 'ž', 'g']
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#
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# def unresonant_silent_consonants():
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# return ['p', 't', 's', 'š', 'č', 'k', 'f', 'h', 'c']
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# test = get_voiced_consonants()
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voiced_consonants = get_voiced_consonants()
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resonant_silent_consonants = get_resonant_silent_consonants()
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unresonant_silent_consonants = get_unresonant_silent_consonants()
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@ -1146,7 +1157,7 @@ def generate_syllable_X_and_y(dictionary, max_word, max_num_vowels, content, vow
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i += 1
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# print(len(X))
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# print(X[0])
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X = np.array(X)
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# X = np.array(X)
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# print(X.shape)
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# print(X[0])
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# print(len(X))
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@ -1174,3 +1185,97 @@ def generate_fake_epoch_syllables(orig_X, orig_X_additional, orig_y, batch_size,
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gen_orig_X = eye[orig_X[loc:loc + batch_size]]
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yield([gen_orig_X, orig_X_additional[loc:loc + batch_size]], orig_y[loc:loc + batch_size])
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loc += batch_size
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def get_max_syllable(syllable_dictionary):
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max_len = 0
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for el in syllable_dictionary:
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if len(el) > max_len:
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max_len = len(el)
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return max_len
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def generate_syllabled_letters_inputs(content_shuffle_vector_location, shuffle_vector_location):
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dictionary, max_word, max_num_vowels, content, vowels, accetuated_vowels = create_dict()
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train_content, test_content, validate_content = split_content(content, 0.2, content_shuffle_vector_location)
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feature_dictionary = create_feature_dictionary()
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print('CREATING SYLLABLE DICTIONARY...')
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syllable_dictionary = create_syllables_dictionary(content, vowels)
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max_syllable = get_max_syllable(syllable_dictionary)
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print('CREATION SUCCESSFUL!')
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# Generate X and y
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print('GENERATING X AND y...')
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X_train, X_other_features_train, y_train = generate_syllable_X_and_y(syllable_dictionary, max_word, max_num_vowels, train_content, vowels,
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accetuated_vowels, feature_dictionary, shuffle_vector_location + '_train.h5')
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X_test, X_other_features_test, y_test = generate_syllable_X_and_y(syllable_dictionary, max_word, max_num_vowels, test_content, vowels,
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accetuated_vowels, feature_dictionary, shuffle_vector_location + '_test.h5')
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X_validate, X_other_features_validate, y_validate = generate_syllable_X_and_y(syllable_dictionary, max_word, max_num_vowels, validate_content,
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vowels, accetuated_vowels, feature_dictionary,
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shuffle_vector_location + '_validate.h5')
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print('GENERATION SUCCESSFUL!')
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return X_train, X_other_features_train, y_train, X_test, X_other_features_test, y_test, X_validate, X_other_features_validate, y_validate
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# generator for inputs for tracking of data fitting
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def generate_fake_epoch_syllabled_letters(orig_X, orig_X_additional, orig_y, batch_size, syllable_letters_translator):
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size = orig_X.shape[0]
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# eye = np.eye(dictionary_size, dtype=int)
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while 1:
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loc = 0
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while loc < size:
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if loc + batch_size >= size:
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# [eye[i] for i in range(size-loc)]
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# gen_orig_X = eye[orig_X[loc:size]]
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# gen_orig_X = [eye[i] for i in range(size-loc)]
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gen_orig_X = syllable_letters_translator[orig_X[loc:size]]
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yield([gen_orig_X, orig_X_additional[loc:size]], orig_y[loc:size])
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else:
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gen_orig_X = syllable_letters_translator[orig_X[loc:loc + batch_size]]
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yield([gen_orig_X, orig_X_additional[loc:loc + batch_size]], orig_y[loc:loc + batch_size])
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loc += batch_size
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def create_syllable_letters_translator(max_syllable, syllable_dictionary, dictionary, vowels, aditional_letter_attributes=True):
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if aditional_letter_attributes:
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voiced_consonants = get_voiced_consonants()
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resonant_silent_consonants = get_resonant_silent_consonants()
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unresonant_silent_consonants = get_unresonant_silent_consonants()
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syllable_letters_translator = []
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for syllable in syllable_dictionary:
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di_syllable = []
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for let in range(max_syllable):
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# di_let = []
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for a in dictionary:
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if let < len(syllable) and a == list(syllable)[let]:
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di_syllable.append(1)
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else:
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di_syllable.append(0)
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if aditional_letter_attributes:
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if let >= len(syllable):
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di_syllable.extend([0, 0, 0, 0, 0, 0])
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elif is_vowel(list(syllable), let, vowels):
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di_syllable.extend([1, 0, 0, 0, 0, 0])
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else:
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# X[i][j][len(dictionary) + 1] = 1
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if list(syllable)[let] in voiced_consonants:
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# X[i][j][len(dictionary) + 2] = 1
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di_syllable.extend([0, 1, 1, 0, 0, 0])
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else:
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# X[i][j][len(dictionary) + 3] = 1
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if list(syllable)[let] in resonant_silent_consonants:
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# X[i][j][len(dictionary) + 4] = 1
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di_syllable.extend([0, 1, 0, 1, 1, 0])
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elif list(syllable)[let] in unresonant_silent_consonants:
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# X[i][j][len(dictionary) + 5] = 1
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di_syllable.extend([0, 1, 0, 1, 0, 1])
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else:
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di_syllable.extend([0, 0, 0, 0, 0, 0])
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# di_syllable.append(di_let)
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syllable_letters_translator.append(di_syllable)
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syllable_letters_translator = np.array(syllable_letters_translator, dtype=int)
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return syllable_letters_translator
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